基于正则总体最小二乘准则的OFDM系统信道估计算法

基于导频的最小二乘(LS)估计方法的优点是结构简单,容易实现,但对噪声和干扰敏感。通过对OFDM系统中由于信道的时变性产生的载波间干扰进行了分析,在此基础上提出正则总体最小二乘(TLS)信道估计算法。根据Tikhonov正则化原理,导出了总体最小二乘正则化解法的计算公式。与一般的LS信道估计相比,TLS方法同时考虑了信道噪声和信道时变特性,所以该算法不仅在一般的信道条件下具有良好的性能而且也适合快变信道条件下的OFDM系统。仿真结果表明,该算法具有很好的均方误差和误比特率性能。     

基于区间二型模糊逻辑的电力负荷预测研究

针对电力负荷具有强随机性而难以准确预测的问题,引入二型模糊逻辑以减小预测误差。建立了区间二型模糊模型用于电力负荷的短期时间序列预测,先利用反向传播算法来调节模型的参数,再利用相似度来精简冗余模糊集合,最后利用奇异值分解法来优选模糊规则。同时,建立了基于反向传播算法的一型模糊模型与区间二型模糊模型,以及基于反向传播-奇异值分解混合迭代算法的区间二型模糊模型,将其预测结果作为检验性能的基准。仿真结果表明,反向传播-相似度-奇异值分解混合迭代算法能够有效地消除冗余模糊集合与模糊规则带来的不良影响,基于其建立的预测模型具有较高的预测精度,能较好地跟踪实际负荷曲线,性能优于另外三个模型。     

A bioinspired touching sensor for amphibious mobile robots

An amphibious mobile robot relies on effective sensing ability to adapt itself in complicated amphibious environments. In this paper, we present a multifunctional whisker-like touching sensor with low energy consumption, inspired by amphibious animals. The sensor comprises a leverage system and a two-dimensional position tracing system, transforming the moving position of biowhisker to a changing laser spot coordinates. On land, the sensor driven by a motor is able to track the movement of biowhisker directly, telling the change of contact position, to sense nearby objects and explore their surface by touching. In underwater environment, the sensor can obtain in real-time external flow direction and velocity by passive impulsion. Testing results showed that our prototype can sense flow or drag force direction in 360° exactly, and tell flow velocity under 1 m/s, it can also recognize line or arc edges of obstacle correctly by touching.     

面向仿真系统的自动测评关键技术研究

面向仿真系统的自动测评通常有基于操作结果和基于操作序列两种方式。基于操作序列的测评方式虽然复杂,但能够全面、客观地反映考生实践操作技能。本文重点介绍操作序列通用框架的表示问题,在此基础上,建立基于专家系统的操作测评模型和实操考核自动评分流程,最后给出自动测评关键技术在航海仪器测评系统中的实际应用,实现了评分结果的相对客观、公正,大大提高了实操考核的工作效率。     

紫外光辐照对脱氧雪腐镰刀菌烯醇和T-2毒素的去除作用

目的：研究紫外光辐照对脱氧雪腐镰刀菌烯醇（deoxynivalenol,DON）和T-2毒素的去除作用。方法：测定不同辐照时间、不同辐照距离、不同pH值条件下紫外光辐照对DON和T-2毒素影响,采用高效液相色谱-质谱联用技术测定毒素及其衍生物,外标法定量。结果：经紫外光辐照后,溶液中DON、T-2毒素的质量浓度均随着辐照时间的延长而不断减小,随着辐照距离和pH值的减小而不断减小。pH 7的1.0 μg/mL DON、T-2毒素溶液,在紫外灯功率20 W、辐照距离150 mm条件下辐照60 min后,DON、T-2毒素去除率分别为（84.90±2.52）%、（74.60±2.74）%。紫外光辐照后,毒素溶液中不含有已知的毒素衍生物,可能被转化成新的未知产物。结论：在非碱性条件下,紫外光辐照对DON、T-2毒素具有明显的去除作用。     

Probability of failure of overloaded lines in cascading failures

Power grids are vulnerable to cascading failures, as shown by previous blackouts or major system disturbances. Line outages due to overload are often the main contributors to the cascading failures leading to these undesired situations. Indeed, the more a line is overloaded, the larger is its sagging, and hence the probability that it will be tripped. It is necessary to quantify in a realistic way the probability of trip as a function of the load in order to compute a good estimation of the frequency of dangerous cascading outages. Several models were proposed for this purpose, but none of them is backed up by empirical evidence or detailed analysis. This paper studies factors that could affect the probability of trip as a function of load, and it computes this probability for two different test systems using a temperature simulation based methodology, called dynamic PRA level-I analysis. This paper then compares existing modelings of this probability to these results. This comparison shows that all modelings used in the literature are not always convenient. We finally propose a simple model that can be adopted in probabilistic risk assessment of cascading failures.     

A novel artificial neural network fire model for prediction of thermal interface location in single compartment fire

Thermal interface is the boundary between the hot and cold gases layers in a compartment fire. The height of the interface depends predominantly on the mass of air entrained into the fire plume. However, the analytical determination of the air mass flow rate is complicated since it is highly nonlinear in nature. Currently, computer models including zone models and field models can be applied to predict fire phenomena effectively. In the zone model computation, the compartment on fire is commonly divided into two layers to which conservation equations are applied to evaluate the fire behaviour. However, the locations of the fire bed and the openings are ignored in the computation. Computational fluid dynamics techniques may be employed, but a major shortcoming is the requirement for extensive computational resources and lengthy computational time. A unique, new and novel artificial neural network (ANN) model, denoted as GRNNFA, is developed for predicting parameters in compartment fires and is an extremely fast alternative approach. The GRNNFA model is capable of capturing the nonlinear system behaviour by training the network using relevant historical data. Since noise is usually embedded in most of the collected fire data, traditional ANN models (e.g. feed-forward multi-layer-perceptron, general regression neural network, radial basis function, etc.) are unable to separate the embedded noise from the genuine characteristics of the system during the course of network training. The GRNNFA has been developed particularly for processing noisy fire data. The model was applied to predict the location of the thermal interface in a single compartment fire and compared with the experiments conducted by Steckler et al. (Flow induced by fire in a compartment, NBSIR 82-2520, National Bureau of Standards, Washington, DC, 1982). The results show that the GRNNFA fire model can predict the location of the thermal interface with up to 94.5% accuracy and minimum computational times and resources. The trained GRNNFA model was also applied to rapidly determine the height of the thermal interface with different locations of fire on the compartment floor and different widths of the opening against field model predictions. Among the five test cases, four of them were predicted well within the minimum error range of the experiment results. It also demonstrated that the prediction accuracy is related to the amount of knowledge provided for network training.     

Determination of interface height from measured parameter profile in enclosure fire experiment

Two methods are proposed in this paper for determining the smoke layer interface height from parameter profiles measured in enclosure fires. The schemes are based on mathematical considerations of uniformity and optimisation, and involve no subjectivity or empiricism. The application of these two methods to a set of experimental data revealed that the two methods gave close results of the interface height but different to that determined with the N-percentage rule. The dependence of the zone average of the measured quantities on the interface height is discussed. The predictions of a two-zone model is also included for comparison.     

基于降雨条件的垃圾污染物释放规律实验研究

为全面系统地研究垃圾污染物释放规律,科学地分析污染物运移规律和预测污染物浓度分布情况。根据阜新市的实际降雨状况,通过垃圾柱的动态淋溶试验,研究了垃圾渗滤液主要污染物:有机物(CODCr)、Cl-、SO42-、总硬度等释放机理。试验结果表明:(CODCr)的衰减曲线方程为:c=9 792.7e-0.103 t,在垃圾中释放速度最快和最慢的分别为Cl-与有机物(CODCr),该试验成果将为阜新垃圾填埋场污染防治提供一定的理论依据。